Defining data science: a new field of inquiry

Data Systems Laboratory, School of Engineering and Applied Sciences Harvard University, Cambridge, MA USA =============DRAFT July 12, 2023 ====================== Data science is not a science. It is a research with which to define, unify, and evolve data paradigm. We benefits - the basis of a comprehensive soluWon have yet to understand and define it. Modern data science is in its infancy. Emerging 1. Challenges defining data science slowly since 1962 and rapidly since 2000, data 1.1. Due to its problem solving techniques is rare. Science and value, power, and scope of applicability, it is modern scienWfic analyses emerged 400 years ago emerging in over 40 disciplines, hundreds of and interpreWvism and interpreWvist analysis 200 research areas, and tens of thousands of years ago. While convenWonal data science is as applicaWons. Yet we are just beginning to old as mathemaWcs, AI-based data science is in its understand and define it. Tukey's 1962 vision of exploratory data publicaWons contain myriad definiWons of data analysis[20][21] brought renewed a`enWon to science and data science problem solving. Aaer its infancy, many definiWons are independent, 2000, machine learning-based data science led to applicaWon-specific, mutually incomplete, a fundamentally new, inscrutable field of inquiry redundant, or inconsistent, hence so is data that we are just beginning to understand. This has led to calls and a data science journal[31] for the data science for a unifying framework to guide unificaWon. An community to achieve such a definiWon. This paper provides candidate definiWons for What is such a unifying framework? How do you essenWal data science arWfacts that are required define a fundamentally new field of inquiry? For to discuss such a definiWon. They are based on the this we look to science, our currently most classical research paradigm concept[15] consisWng powerful knowledge discovery paradigm. of a philosophy of data science, the data science problem solving paradigm, and the six component 1.2. ACM lists 200+ data science journals. This required paradigms that were and Aristotle (384-322 BC)) then in terms of accepted by scienWsts to guide the unificaWon of scienWfic models, theories, and the scienWfic the myriad definiWons based on established method by Francis Bacon [Novum Organum 1620] results.